Bayesian super-resolution of text image sequences from low resolution observations

Author

Cortijo, Francisco J. ; Villena, Salvador ; Molina, Rafael ; Katsaggelos, Aggelos

Author_Institution

Dpto. de Ciencias de la Computacion, Univ. de Granada, Spain

Volume

1

fYear

2003

fDate

1-4 July 2003

Firstpage

421

Abstract

This paper deals with the problem of reconstructing high-resolution text images from an incomplete set of under-sampled, blurred, and noisy images shifted with subpixel displacement. We derive mathematical expressions for the calculation of the maximum a posteriori estimate of the high resolution image and the estimation of the parameters involved in the model. The method is tested on real text images and car plates, examining the impact of blurring and the number of available low resolution images on the final estimate.

Keywords

image reconstruction; image resolution; image sampling; image sequences; maximum likelihood estimation; Bayesian super-resolution; image blurring; image reconstruction; image sampling; maximum a posteriori estimation; noisy image; parameter estimation; text image sequence; Bayesian methods; Charge coupled devices; Image reconstruction; Image resolution; Image sensors; Image sequences; Optical noise; Optical sensors; Signal resolution; Signal to noise ratio;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Its Applications, 2003. Proceedings. Seventh International Symposium on

Print_ISBN

0-7803-7946-2

Type

conf

DOI

10.1109/ISSPA.2003.1224730

Filename

1224730